GEO series

Regulation of Cortical Neurogenesis by MED13L via Transcriptional Priming and its Implications for MED13L Syndrome

GSE277054 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/06/30 Platform GPL24247Platform GPL34290

At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Mus musculus (mouse)
Samples: 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper: Regulation of cortical neurogenesis by MED13L via transcriptional priming and its implications for MED13L syndromeCommunications biology · 2025

Summary (written by the submitters)

MED13L is highly susceptible to neurodevelopmental disorders, yet the underlying developmental mechanisms remain poorly understood. We developed a gene knockout mouse model of MED13L syndrome to elucidate these mechanisms. Homozygous Med13l-null mice exhibit neonatal lethality and severe cortical neurogenesis deficits due to impaired differentiation of neural progenitors.

Read the full summary ↓

In contrast, heterozygous Med13l-null mice are viable but display characteristic behavioral deficits of MED13L syndrome, including impaired learning and memory, reduced motor coordination, and heightened anxiety. Heterozygous mice also present with microcephaly and simplified neuronal morphology in the motor cortex. Conditional knockout of Med13l in the forebrain pyramidal lineage corroborated the motor and histological deficits observed. Proteomic, transcriptomic, and single-cell RNA sequencing analyses suggest that MED13L regulates cortical neurogenesis by priming developmental genes for transcriptional activation as a component of the mediator complex. These findings provide insights into the molecular and neurodevelopmental underpinnings of MED13L syndrome, paving the way for potential therapeutic strategies.

Published in

Regulation of cortical neurogenesis by MED13L via transcriptional priming and its implications for MED13L syndrome

Li J, Hao YZ, Cui J et al. · Communications biology 2025 · PMID 40775066 · doi:10.1038/s42003-025-08532-8

This dataset

Open GSE277054 in finder → Find more mouse RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE277054_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1160297 and SRA study SRP532358. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40775066) ↗

Study design

12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM8513198 Med13L WT1_cortex_E13.5, bulk RNA
GSM8513199 Med13L WT2_cortex_E13.5, bulk RNA
GSM8513200 Med13L WT3_cortex_E13.5, bulk RNA
GSM8513201 Med13L Het1_cortex_E13.5, bulk RNA
GSM8513202 Med13L Het2_cortex_E13.5, bulk RNA
GSM8513203 Med13L Het3_cortex_E13.5, bulk RNA
GSM8513204 Med13L KO1_cortex_E13.5, bulk RNA
GSM8513205 Med13L KO2_cortex_E13.5, bulk RNA
GSM8513206 Med13L KO3_cortex_E13.5, bulk RNA
GSM8513207 Med13L WT_cortex_E13.5, scRNA
GSM8513208 Med13L Het_cortex_E13.5, scRNA
GSM8513209 Med13L KO_cortex_E13.5, scRNA

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.